Logistics shuttle path optimization method and system based on ant colony optimization algorithm

Abstract

This invention provides a method and system for optimizing logistics shuttle routes based on ant colony optimization algorithm, relating to the field of route optimization technology. The method includes: allocating orders to logistics shuttles; setting up sub-simulation vehicles; constructing multiple routes using the sub-simulation vehicles and leaving time markers; assigning importance levels to each route; obtaining the priority order of logistics shuttles; and optimizing the routes of logistics shuttles according to the priority order. This invention addresses the problem in existing technologies where logistics shuttle route optimization cannot determine whether a logistics shuttle should change routes or stop and wait when route conflicts occur, leading to reduced logistics transportation efficiency due to logistics shuttles choosing time-consuming collision avoidance methods.

Description

Technical Field

[0001] The present invention relates to the technical field of path optimization, and in particular to a logistics shuttle path optimization method and system based on an ant colony optimization algorithm. Background Art

[0002] The ant colony optimization algorithm is an optimization algorithm that simulates the foraging behavior of ants. Its basic principle is to use the pheromones left by ants in the process of looking for food to guide the behavior of other ants, so as to find the optimal path. In the process of looking for food, ants will leave pheromones on the path. The pheromone concentration on the shorter path is higher, which attracts more ants to choose this path, and finally forms a positive feedback mechanism, so that all ants are concentrated on the optimal path. The application of the ant colony optimization algorithm is very wide, and it can be used to solve a variety of complex optimization problems, such as the traveling salesman problem (TSP), vehicle path planning, network routing optimization, etc. The logistics shuttle is an intelligent handling robot and a core automation equipment for pallet-intensive storage systems. It can realize tasks such as warehousing, inventory, and placement of goods under the control of the system, and can communicate with the host computer, WMS system or be controlled by a handheld terminal, and realize the functions of automatic identification and automatic storage and retrieval by combining technologies such as electronic tags and barcodes. The path optimization of the logistics shuttle refers to the process of scientifically and rationally planning and optimizing the operation path of the logistics shuttle in the process of logistics distribution, so as to achieve the goals of improving logistics distribution efficiency, reducing costs, and reducing time and resource waste.

[0003] Existing methods for optimizing the path of logistics shuttle vehicles are usually applied to the acquisition of the shortest path of logistics shuttle vehicles and collision avoidance. For example, by establishing an optimization model and using an algorithm, the path planning and optimization of the logistics shuttle vehicle are realized, and the collision of the logistics shuttle vehicle is avoided during the path optimization. However, in terms of avoiding the collision of the logistics shuttle vehicle, it is usually directly set to change the path or stop and wait. However, there is a lack of effective improvement in judging whether the logistics shuttle vehicle should change the path or stop and wait. This will result in that when the logistics shuttle vehicle only needs to wait for a short time, the collision avoidance processing method is to change the path, causing the logistics shuttle vehicle to take a long detour and consume a long time, thereby reducing the working efficiency of the logistics shuttle vehicle. For example, in the publication number CN117495223A In the patent application, a warehouse logistics optimization method for multiple two-way shuttle vehicles operating in the same area is disclosed. The solution is to use the A* algorithm to plan the optimal driving path for each two-way shuttle vehicle and avoid collisions. Other methods for path optimization of logistics shuttle vehicles are usually improved on the production line. Through a more reasonable production line arrangement, the path optimization of the logistics shuttle vehicles is achieved. However, this improved method still cannot determine whether the logistics shuttle vehicle should change its path or stop and wait when a conflict occurs in the path of the logistics shuttle vehicle. As a result, the logistics shuttle vehicle chooses a time-consuming way to avoid collisions, which reduces the logistics transportation efficiency. In view of this, it is necessary to improve the existing methods for path optimization of logistics shuttle vehicles. Summary of the invention

[0004] In view of the shortcomings of the prior art, the purpose of the present invention is to provide a logistics shuttle path optimization method and system based on an ant colony optimization algorithm. By proposing a logistics shuttle path optimization method and system based on an ant colony optimization algorithm, it is used to solve the problem that the existing improvements in the path optimization of logistics shuttles are unable to determine whether the logistics shuttle should change its path or stop and wait when a conflict occurs on the path of the logistics shuttle, resulting in a reduction in logistics transportation efficiency due to the logistics shuttle choosing a time-consuming method to avoid collisions.

[0005] In order to achieve the above object, the present invention is implemented through the following technical solutions:

[0006] In a first aspect, the present invention provides a logistics shuttle path optimization method based on an ant colony optimization algorithm, comprising the following steps:

[0007] Step S1: Obtain logistics orders in real time and allocate orders to logistics shuttle vehicles;

[0008] Step S2: setting up sub-simulation vehicles for all logistics shuttle vehicles;

[0009] Step S3: construct multiple paths using the sub-simulated vehicles and leave time marks;

[0010] Step S4: Calculate the length of the path passed by each sub-simulation vehicle and set an importance level for each path;

[0011] Step S5: Obtain the priority order of the logistics shuttle vehicles, and optimize the paths of the logistics shuttle vehicles according to the priority order of the logistics shuttle vehicles.

[0012] Furthermore, the step S1 includes the following sub-steps:

[0013] Step S101: Obtain logistics orders, and sort the logistics orders in the order of time when the logistics orders are obtained;

[0014] Step S102: Obtain the pickup location and delivery location in the logistics order, obtain the real-time location of the logistics shuttle in the storage area, and assign the logistics order to the logistics shuttle closest to the pickup location of the logistics order in chronological order;

[0015] Step S103: Set the current position of the logistics shuttle as the starting point of the logistics shuttle, set the pickup position of the logistics order as the stop point of the logistics shuttle, and set the delivery position of the logistics order as the end point of the logistics shuttle.

[0016] Furthermore, the step S2 includes the following sub-steps:

[0017] Step S201: Real-time acquisition of the number of logistics shuttles in the storage area, marking the logistics shuttles, and obtaining the logistics shuttles CS1 to CS2. n ;

[0018] Step S202: Logistics shuttle CS1 to logistics shuttle CS n Set up m sub-simulation cars respectively, marked as CS i -Z1 to CS i -Z m , where the value of i ranges from 1 to n.

[0019] Furthermore, the step S3 includes the following sub-steps:

[0020] Step S301: Obtain a plan view of the storage area, obtain the path that the logistics shuttle vehicle can pass through in the storage area, and obtain a map to be planned;

[0021] Step S302: Get any logistics shuttle CS i The starting point, stop point and end point;

[0022] Step S303: Obtain the logistics shuttle CS i All paths from the starting point to the stop point are set as a path;

[0023] Get Logistics Shuttle CS i All paths from the stop point to the end point are set as two-segment paths;

[0024] Get all combinations of the first path and the second path to get the sub-simulation path, and arrange an arbitrary sub-simulation car CS for each sub-simulation path i -Z l ; Wherein, the value of l ranges from 1 to m;

[0025] Step S304: For any sub-simulated vehicle CS i -Z l The time of the trip on the sub-simulation path is recorded to obtain a time mark.

[0026] Furthermore, the moment record in step S304 includes a plane mark and a z-axis mark, and the plane mark includes: obtaining the logistics shuttle CS i Body length, when any sub-simulation car CS i -Z l Each distance traveled on the plane of the sub-simulation path is equal to the logistics shuttle CS i When the path is the length of the vehicle body, the path is recorded as a plane grid, and a plane time mark is left for the plane grid. The plane time mark is the sub-simulation vehicle CS i -Z l The time point of entering the plane grid; until all the paths on the plane of the path are recorded as plane grids and leave plane time marks;

[0027] The z-axis marking includes: obtaining the logistics shuttle CS i Vehicle height, when any sub-simulation vehicle CS i -Z l Each distance traveled on the z-axis path of the sub-simulation path is equal to the logistics shuttle CS i When the path of the vehicle body height is recorded, the path is recorded as a z-axis square, and a z-axis time mark is left for the z-axis square. The z-axis time mark is the sub-simulation vehicle CS i -Z l The time point of entering the z-axis grid; until all z-axis paths of the path are recorded as z-axis squares and leave z-axis time marks.

[0028] Furthermore, the step S4 includes the following sub-steps:

[0029] Step S401: obtaining the number of squares on each sub-simulation path and recording it as the path length of the sub-simulation path, wherein the squares include z-axis squares and plane squares;

[0030] Step S402: Obtain the path lengths of all sub-simulation paths, sort the path lengths in ascending order, and mark the importance level for each sub-simulation path according to the sorting;

[0031] Step S403: Obtain the first number of sub-simulation paths with the highest importance level for each logistics shuttle vehicle, mark them on the map to be planned, and obtain a simulation map.

[0032] Furthermore, the step S5 includes the following sub-steps:

[0033] Step S501: Obtain the time sequence of the logistics orders received by all logistics shuttles, and set the time sequence of the logistics orders as the priority sequence of the logistics shuttles;

[0034] Step S502: setting the sub-simulation path with the highest importance level of the logistics shuttle vehicle with the highest current priority order as the first-level path, and obtaining the time marks of all the squares on the first-level path;

[0035] Step S503: when the time marks of all squares on the primary path are independent and different, the primary path is retained and set as the preferred path, and the logistics shuttle with the highest priority is removed from the priority order of the logistics shuttles;

[0036] When the same time mark appears on any square on the primary path, the primary path is retained and set as the preferred path, the square is set as a divergence square, all sub-simulation paths corresponding to the same time mark are set as secondary paths, and the secondary paths are optimized to obtain a secondary path cancellation signal or a secondary path delay signal;

[0037] Step S504: when a secondary path cancellation signal is received, after deleting the secondary path, the logistics shuttle with the highest current priority order is removed from the priority order of logistics shuttles;

[0038] When a secondary path delay signal is received, the secondary path obtained after the delay modification is set as the preferred path of the corresponding logistics shuttle, and the logistics shuttle with the highest current priority and the logistics shuttle corresponding to the secondary path are removed from the priority order of the logistics shuttle;

[0039] Step S505: Repeat steps S501 to S504 until all logistics shuttles are removed from the priority order of logistics shuttles.

[0040] Furthermore, the secondary path optimization includes obtaining a logistics shuttle vehicle corresponding to any secondary path, obtaining the shortest path of the logistics shuttle vehicle on the simulation map, and recording the time of the marking moment on the last square of the shortest path as the route switching time;

[0041] Obtain any secondary path, and set an extension time for the secondary path, where the extension time is the difference between the time mark of the next square of the divergent square on the primary path and the time mark on the divergent square;

[0042] Performing a delay modification on the time mark on the square behind the divergent square on the secondary path, wherein the delay modification includes adding an extended time to the time of the original time mark, and setting the time mark obtained after the delay modification as a secondary mark;

[0043] The time to obtain the secondary mark of the last square on the secondary path is recorded as the waiting time;

[0044] When the switching time is earlier than the waiting time, a secondary path cancellation signal is sent;

[0045] When the route switching time is later than the waiting time, the modified secondary path is merged into the simulation map, and it is determined whether the secondary path obtained after the delay modification has the same time mark as other simulation paths on the simulation map;

[0046] When the secondary path obtained after the delay modification does not have the same time mark as other simulated paths on the simulated map, a secondary path delay signal is sent;

[0047] When the secondary path obtained after delay modification appears at the same time mark as other simulated paths on the simulated map, a secondary path cancellation signal is sent.

[0048] In a second aspect, the present invention provides a logistics shuttle path optimization system based on an ant colony optimization algorithm, comprising: a logistics allocation module, a path collection module, a path marking module and a path optimization module;

[0049] The logistics distribution module is used to distribute logistics orders to logistics shuttle vehicles;

[0050] The path acquisition module is used to set up a sub-simulation vehicle for the logistics shuttle vehicle and use the sub-simulation vehicle to construct a simulation path;

[0051] The path marking module is used to mark the simulation path to obtain the time mark and the importance level of the simulation path;

[0052] The path optimization module is used to obtain the priority order of the logistics shuttle vehicles and optimize the paths of the logistics shuttle vehicles according to the priority order of the logistics shuttle vehicles.

[0053] Beneficial effects of the present invention: The present invention first obtains logistics orders in real time and distributes orders to logistics shuttle vehicles; sets sub-simulation vehicles for all logistics shuttle vehicles; uses sub-simulation vehicles to construct multiple paths and leaves time marks. The advantage of this is that by using the sub-simulation vehicles of the logistics shuttle vehicles to obtain the time marks corresponding to multiple paths, it is helpful to obtain conflicting transportation paths in time during the actual logistics shuttle vehicle transportation, so as to perform path analysis in time, reduce the invalid waiting or invalid movement time of the logistics shuttle vehicles, and improve the efficiency of judging whether the logistics shuttle vehicles should change the path or stop to wait;

[0054] The present invention also sets an importance level for each path; obtains the priority order of the logistics shuttle vehicles, and optimizes the paths of the logistics shuttle vehicles according to the priority order of the logistics shuttle vehicles. The advantage of this is that by optimizing the paths based on the importance level of each path and the priority order of the logistics shuttle vehicles, it can ensure that the paths of the logistics shuttle vehicles for logistics transmission are all optimal paths. At the same time, when there is a path conflict of the logistics shuttle vehicles, the path optimization can obtain the solution with the shortest time for changing the path or stopping and waiting, thereby improving the overall transportation efficiency of the logistics shuttle vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0056] Figure 1 is a flow chart of the method steps of the present invention;

[0057] Figure 2 It is a system principle block diagram of the present invention. DETAILED DESCRIPTION

[0058] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0059] It should be noted that the terms used herein are for describing specific embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0060] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0061] Example 1, please refer to Figure 1 As shown, the present invention provides a logistics shuttle path optimization method based on an ant colony optimization algorithm, comprising the following steps:

[0062] Step S1: Obtain logistics orders in real time and allocate orders to logistics shuttle vehicles;

[0063] Step S1 includes the following sub-steps: Step S101: Obtain logistics orders, and sort the logistics orders in the order of time when the logistics orders are obtained; in the specific implementation process, the logistics order includes the pickup location of the order at the order time and the delivery location of the order. For example, the order time of a logistics order is 12:00, the pickup location of the order is at position 2 on the first floor of shelf 3, and the target location of the order is position 1 on the first floor of shelf 1;

[0064] Step S102: Obtain the pickup location and delivery location in the logistics order, obtain the real-time location of the logistics shuttle in the storage area, and assign the logistics order to the logistics shuttle closest to the pickup location of the logistics order in chronological order; in the specific implementation process, for example, the pickup location of a logistics order is No. 2, 1st floor, No. 3 shelf, and the order time is 12:00, and the pickup location of another logistics order is No. 1, 1st floor, No. 1 shelf, and the order time is 12:10,

[0065] There is also a logistics shuttle at position 3 on the first floor of shelf 3 and a logistics shuttle at position 5 on the second floor of shelf 3.

[0066] Then the logistics order with the pickup location of No. 2 on the 1st floor of Shelf 3 and the order time of 12:00 is assigned to the logistics shuttle vehicle at No. 3 on the 1st floor of Shelf 3, and the logistics order with the pickup location of No. 1 on the 1st floor of Shelf 3 and the order time of 12:10 is assigned to the logistics shuttle vehicle at No. 5 on the 2nd floor of Shelf 3;

[0067] Step S103: Set the current position of the logistics shuttle as the starting point of the logistics shuttle, set the pick-up position of the logistics order as the stop point of the logistics shuttle, and set the delivery position of the logistics order as the end point of the logistics shuttle; in the specific implementation process, for example, when the logistics shuttle at position 3 on the 1st floor of shelf 3 is assigned to a logistics order with the pick-up position being position 2 on the 1st floor of shelf 3 and the delivery position being position 1 on the 1st floor of shelf 1, then the starting point of the logistics shuttle is position 3 on the 1st floor of shelf 3, the stop point is position 2 on the 1st floor of shelf 3, and the end point is position 1 on the 1st floor of shelf 1.

[0068] Step S2: Set up sub-simulation vehicles for all logistics shuttle vehicles; Step S2 includes the following sub-steps: Step S201: Real-time acquisition of the number of logistics shuttle vehicles in the storage area, marking the logistics shuttle vehicles, and obtaining the logistics shuttle vehicles CS1 to CS2. n ; In the specific implementation process, for example, if the number of logistics shuttles in the storage area is 4, then the logistics shuttle CS1, logistics shuttle CS2, logistics shuttle CS3 and logistics shuttle CS4 are marked;

[0069] Step S202: Logistics shuttle CS1 to logistics shuttle CS n Set up m sub-simulation cars respectively, marked as CS i -Z1 to CS i -Z m , where i ranges from 1 to n. In the specific implementation process, the value of m defaults to infinity, which varies according to the number of paths constructed by the sub-simulated car. When the number of paths constructed by the sub-simulated car is 5, the value of m is 5.

[0070] Step S3: Use the sub-simulation vehicle to construct multiple paths and leave time marks; Step S3 includes the following sub-steps: Step S301: Obtain a plan view of the storage area, obtain the path that the logistics shuttle vehicle can pass through in the storage area, and obtain a map to be planned;

[0071] Step S302: Get any logistics shuttle CS i The starting point, stop point and end point;

[0072] Step S303: Obtain the logistics shuttle CS i All paths from the starting point to the stop point are set as a path; in the specific implementation process, for example, the logistics shuttle CS i The starting point, stop point and end point are position 2 on the 1st floor of rack 3, position 5 on the 1st floor of rack 3 and position 9 on the 1st floor of rack 3 respectively. Then one of the first-stage paths can be: first from position 2 on the 1st floor of rack 3 to position 3 on the 1st floor of rack 3, then from position 3 on the 1st floor of rack 3 to position 4 on the 1st floor of rack 3, and finally from position 4 on the 1st floor of rack 3 to position 5 on the 1st floor of rack 3; one of the second-stage paths can be: first from position 5 on the 1st floor of rack 3 to position 6 on the 1st floor of rack 3, then from position 6 on the 1st floor of rack 3 to position 7 on the 1st floor of rack 3, from position 7 on the 1st floor of rack 3 to position 8 on the 1st floor of rack 3, and finally from position 8 on the 1st floor of rack 3 to position 9 on the 1st floor of rack 3;

[0073] Get Logistics Shuttle CS i All paths from the stop point to the end point are set as two-segment paths;

[0074] Get all combinations of the first path and the second path to get the sub-simulation path, and arrange an arbitrary sub-simulation car CS for each sub-simulation path i -Z l ; Wherein, the value of l ranges from 1 to m;

[0075] Step S304: For any sub-simulated vehicle CS i -Z l Record the time of the trip on the sub-simulation path to obtain a time mark;

[0076] The moment record in step S304 includes plane marking and z-axis marking. The plane marking includes: obtaining the logistics shuttle CS i Body length, when any sub-simulation car CS i -Z l Each distance traveled on the plane of the sub-simulation path is equal to the logistics shuttle CS i When the path is the length of the vehicle body, the path is recorded as a plane grid, and a plane time mark is left for the plane grid. The plane time mark is the sub-simulation vehicle CS i -Z l The time point of entering the plane grid; until all the paths on the plane of the path are all recorded as plane grids and leave plane time marks; in the specific implementation process, for example, the sub-simulation vehicle CS i -Z l The length of the body of the sub-simulation vehicle CS is 1 meter. i -Z l Every time 1 meter is traveled on the sub-simulation path, the 1 meter traveled is recorded as a plane square, and the sub-simulation vehicle CS is obtained through data acquisition. i -Z l If the time of entering the plane grid is 11:00, the plane time mark left on the plane grid is 11:00. The scheme for recording the time can be based on the technology of releasing pheromones in the ant colony optimization algorithm, leaving a time mark to facilitate the calculation of the path duration, so as to select the shortest time path;

[0077] The z-axis marking includes: obtaining the height of the logistics shuttle vehicle CSi, when any sub-simulation vehicle CS i -Z l Each distance traveled on the z-axis path of the sub-simulation path is equal to the logistics shuttle CS i When the path of the vehicle height is measured, the path is recorded as a z-axis square, and a z-axis time mark is left for the z-axis square. The z-axis time mark is the sub-simulation vehicle CS i -Z l The time point of entering the z-axis grid; until all z-axis paths of the path are recorded as z-axis grids and leave z-axis time marks; in the specific implementation process, for example, the sub-simulation car CS i -Z l The height of the vehicle body is 20cm. i -Z l When the sub-simulation vehicle CS is obtained by data acquisition, the path is recorded as a z-axis square when it travels 20 cm on the z-axis path. i -Z l If the time of entering the z-axis square is 12:00, the z-axis time mark left in the z-axis square is 12:00.

[0078] Step S4: Calculate the path length of each sub-simulation vehicle and set an importance level for each path; Step S4 includes the following sub-steps: Step S401: Obtain the number of squares on each sub-simulation path and record it as the path length of the sub-simulation path, where the squares include z-axis squares and plane squares;

[0079] Step S402: Obtain the path lengths of all sub-simulation paths, sort the path lengths in order from small to large, and mark the importance level for each sub-simulation path according to the sorting; in a specific implementation process, for example, after sorting the lengths, the lengths of all paths are 3, 5, 10, 12, and 20 in order, then the importance levels of the sub-simulation paths are from high to low: a sub-simulation path with a path length of 3, a sub-simulation path with a path length of 5, a sub-simulation path with a path length of 10, a sub-simulation path with a path length of 12, and a sub-simulation path with a path length of 20;

[0080] Step S403: Obtain the first number of sub-simulation paths with the highest importance level for each logistics shuttle vehicle, mark them on the map to be planned, and obtain a simulation map.

[0081] Step S5: Obtain the priority order of the logistics shuttle vehicles, and optimize the paths of the logistics shuttle vehicles according to the priority order of the logistics shuttle vehicles;

[0082] Step S5 includes the following sub-steps: Step S501: Obtain the time sequence of the logistics orders received by all logistics shuttles, and set the time sequence of the logistics orders as the priority sequence of the logistics shuttles;

[0083] Step S502: setting the sub-simulation path with the highest importance level of the logistics shuttle vehicle with the highest current priority order as the first-level path, and obtaining the time marks of all the squares on the first-level path;

[0084] Step S503: when the time marks of all squares on the primary path are independent and different, the primary path is retained and set as the preferred path, and the logistics shuttle with the highest priority is removed from the priority order of the logistics shuttles;

[0085] When the same time mark appears on any square on the primary path, the primary path is retained and set as the preferred path, the square is set as a divergent square, all sub-simulation paths corresponding to the same time mark are set as secondary paths, and the secondary paths are optimized to obtain a secondary path cancellation signal or a secondary path delay signal; the secondary path optimization includes obtaining a logistics shuttle vehicle corresponding to any secondary path, obtaining the shortest path of the logistics shuttle vehicle on the simulation map, and recording the time of the marked moment on the last square of the shortest path as the route switching time; in the specific implementation process, for example, if the last square of the shortest path is a z-axis square, and the z-axis time mark of the z-axis square is 12:00, the route switching time is recorded as 12:00;

[0086] Get any secondary path, set an extension time for the secondary path, and the extension time is the difference between the time mark of the next square of the divergence square on the primary path and the time mark on the divergence square; in the specific implementation process, for example, the time mark of the next square of the analysis square on a secondary path is 12:10, and the time mark on the divergence square is 12:00, then the extension time can be calculated to be 10 minutes;

[0087] Performing a delayed modification on the time mark on the square behind the divergent square on the secondary path, wherein the delayed modification includes adding an extended time to the original time mark, and setting the time mark obtained after the delayed modification as the secondary mark;

[0088] The time to obtain the secondary mark of the last square on the secondary path is recorded as the waiting time;

[0089] When the switching time is earlier than the waiting time, a secondary path cancellation signal is sent;

[0090] When the route switching time is later than the waiting time, the modified secondary path is merged into the simulation map, and it is determined whether the secondary path obtained after the delay modification has the same time mark as other simulation paths on the simulation map;

[0091] When the secondary path obtained after the delay modification does not have the same time mark as other simulated paths on the simulated map, a secondary path delay signal is sent;

[0092] In the specific implementation process, for example, in one analysis, the route switching time is 12:30 and the waiting time is 12:00, then the route switching time is later than the waiting time, so a delay modification is performed, and the secondary path obtained after the delay modification has the same time mark as other simulated paths on the simulation map, then a secondary path cancellation signal is sent; when the route switching time is later than the waiting time, by performing a delay modification and making a judgment on the same path, it is possible to judge whether the logistics shuttle vehicle should wait or change the path, thereby improving the cargo transportation efficiency of the logistics shuttle vehicle;

[0093] When the secondary path obtained after delay modification appears at the same time mark as other simulated paths on the simulated map, a secondary path cancellation signal is sent.

[0094] Step S504: when a secondary path cancellation signal is received, after deleting the secondary path, the logistics shuttle with the highest current priority order is removed from the priority order of logistics shuttles;

[0095] When a secondary path delay signal is received, the secondary path obtained after the delay modification is set as the preferred path of the corresponding logistics shuttle, and the logistics shuttle with the highest current priority and the logistics shuttle corresponding to the secondary path are removed from the priority order of the logistics shuttle;

[0096] Step S505: Repeat steps S501 to S504 until all logistics shuttles are removed from the priority order of logistics shuttles.

[0097] Example 2, please refer to Figure 2 As shown, the present invention provides a logistics shuttle path optimization system based on an ant colony optimization algorithm, the system comprising: a logistics allocation module, a path collection module, a path marking module and a path optimization module;

[0098] The logistics distribution module is used to distribute logistics orders to the logistics shuttle vehicles; the logistics distribution module includes a logistics distribution unit, and the logistics distribution unit is configured with a logistics distribution strategy, and the logistics distribution strategy includes: obtaining logistics orders, and sorting the logistics orders according to the time sequence of obtaining the logistics orders;

[0099] Obtain the pickup location and delivery location in the logistics order, obtain the real-time location of the logistics shuttle in the storage area, and assign the logistics order to the logistics shuttle closest to the pickup location of the logistics order in chronological order;

[0100] Set the current position of the logistics shuttle as the starting point of the logistics shuttle, set the pickup location of the logistics order as the stop point of the logistics shuttle, and set the delivery location of the logistics order as the end point of the logistics shuttle.

[0101] The path collection module is used to set up a sub-simulation vehicle for the logistics shuttle vehicle and use the sub-simulation vehicle to construct a simulation path; the path collection module includes a path collection unit, and the path collection unit is configured with a path collection strategy. The path collection strategy includes: real-time acquisition of the number of logistics shuttle vehicles in the storage area, marking the logistics shuttle vehicles, and obtaining the logistics shuttle vehicle CS1 to the logistics shuttle vehicle CS n ; Logistics shuttle CS1 to logistics shuttle CS n Set up m sub-simulation cars respectively, marked as CS i -Z1 to CS i-Z m , where the value of i ranges from 1 to n;

[0102] Obtain the floor plan of the storage area, obtain the paths that the logistics shuttle vehicles can pass through in the storage area, and obtain the map to be planned;

[0103] Get any logistics shuttle CS i The starting point, stop point and end point;

[0104] Get Logistics Shuttle CS i All paths from the starting point to the stop point are set as a path;

[0105] Get Logistics Shuttle CS i All paths from the stop point to the end point are set as two-segment paths;

[0106] Get all combinations of the first path and the second path to get the sub-simulation path, and arrange an arbitrary sub-simulation car CS for each sub-simulation path i -Z l ; Wherein, the value of l ranges from 1 to m;

[0107] For any sub-simulation car CS i -Z l The time record of the trip on the sub-simulation path is obtained to obtain the time mark; the time record includes the plane mark and the z-axis mark. The plane mark includes: Get the logistics shuttle CS i Body length, when any sub-simulation car CS i -Z l Each distance traveled on the plane of the sub-simulation path is equal to the logistics shuttle CS i When the path is the length of the vehicle body, the path is recorded as a plane grid, and a plane time mark is left for the plane grid. The plane time mark is the sub-simulation vehicle CS i -Z l The time point of entering the plane grid; until all the paths on the plane of the path are recorded as plane grids and leave plane time marks;

[0108] The z-axis markings include: Get the logistics shuttle CS i Vehicle height, when any sub-simulation vehicle CS i -Z l Each distance traveled on the z-axis path of the sub-simulation path is equal to the logistics shuttle CS i When the path of the vehicle body height is recorded, the path is recorded as a z-axis square, and a z-axis time mark is left for the z-axis square. The z-axis time mark is the sub-simulation vehicle CS i -Z lThe time point of entering the z-axis grid; until all z-axis paths of the path are recorded as z-axis squares and leave z-axis time marks.

[0109] The path marking module is used to mark the simulation path to obtain the time mark and the importance level of the simulation path; the path marking module includes a path marking unit, and the path marking unit is configured with a path marking strategy, and the path marking strategy includes: obtaining the number of squares on each sub-simulation path, and recording it as the path length of the sub-simulation path, and the squares include z-axis squares and plane squares;

[0110] Obtain the path lengths of all sub-simulation paths, sort the path lengths in ascending order, and mark the importance level of each sub-simulation path according to the sorting;

[0111] The first number of sub-simulation paths with the highest importance level for each logistics shuttle vehicle is obtained, and they are marked on the map to be planned to obtain a simulation map.

[0112] The path optimization module is used to obtain the priority sequence of the logistics shuttle vehicles, and optimize the paths of the logistics shuttle vehicles according to the priority sequence of the logistics shuttle vehicles; the path optimization module includes a path optimization unit, and the path optimization unit is configured with a path optimization strategy, and the path optimization strategy includes: obtaining the time sequence of the logistics orders received by all logistics shuttle vehicles, and setting the time sequence of the logistics orders as the priority sequence of the logistics shuttle vehicles;

[0113] The sub-simulation path with the highest importance level and the logistics shuttle with the highest current priority is set as the first-level path, and the time marks of all the squares on the first-level path are obtained;

[0114] When the time marks of all squares on the primary path are independent and different, the primary path is retained and set as the preferred path, and the logistics shuttle with the highest priority is removed from the priority order of the logistics shuttle;

[0115] When the same time mark appears on any square on the primary path, the primary path is retained and set as the preferred path, the square is set as a divergent square, all sub-simulation paths corresponding to the same time mark are set as secondary paths, and the secondary paths are optimized to obtain a secondary path cancellation signal or a secondary path delay signal; the secondary path optimization includes obtaining a logistics shuttle vehicle corresponding to any secondary path, obtaining the shortest path of the logistics shuttle vehicle on the simulation map, and recording the time of the mark on the last square of the shortest path as the route switching time;

[0116] Get any secondary path, set an extension time for the secondary path, and the extension time is the difference between the time mark of the next square of the divergent square on the primary path and the time mark on the divergent square;

[0117] Performing a delayed modification on the time mark on the square behind the divergent square on the secondary path, wherein the delayed modification includes adding an extended time to the original time mark, and setting the time mark obtained after the delayed modification as the secondary mark;

[0118] The time to obtain the secondary mark of the last square on the secondary path is recorded as the waiting time;

[0119] When the switching time is earlier than the waiting time, a secondary path cancellation signal is sent;

[0120] When the route switching time is later than the waiting time, the modified secondary path is merged into the simulation map, and it is determined whether the secondary path obtained after the delay modification has the same time mark as other simulation paths on the simulation map;

[0121] When the secondary path obtained after the delay modification does not have the same time mark as other simulated paths on the simulated map, a secondary path delay signal is sent;

[0122] When the secondary path obtained after delay modification and other simulated paths on the simulated map appear at the same time mark, a secondary path cancellation signal is sent;

[0123] When a secondary path cancellation signal is received, after deleting the secondary path, the logistics shuttle with the highest current priority order is removed from the priority order of the logistics shuttles;

[0124] When a secondary path delay signal is received, the secondary path obtained after the delay modification is set as the preferred path of the corresponding logistics shuttle, and the logistics shuttle with the highest current priority and the logistics shuttle corresponding to the secondary path are removed from the priority order of the logistics shuttle;

[0125] The routing optimization strategy is repeated until all logistics shuttles are removed from the logistics shuttle priority order.

[0126] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program codes. Among them, the storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, magnetic disk or optical disk. These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0127] The above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A logistics shuttle path optimization method based on ant colony optimization algorithm, characterized in that: The steps include: Step S1: Obtain logistics orders in real time and allocate orders to logistics shuttle vehicles; Step S2: setting up sub-simulation vehicles for all logistics shuttle vehicles; Step S3: construct multiple paths using the sub-simulated vehicles and leave time marks; Step S4: Calculate the length of the path passed by each sub-simulation vehicle and set an importance level for each path; Step S5: Obtain the priority order of the logistics shuttle vehicles, and optimize the paths of the logistics shuttle vehicles according to the priority order of the logistics shuttle vehicles; The step S1 includes the following sub-steps: Step S101: Obtain logistics orders, and sort the logistics orders in the order of time when the logistics orders are obtained; Step S102: Obtain the pickup location and delivery location in the logistics order, obtain the real-time location of the logistics shuttle in the storage area, and assign the logistics order to the logistics shuttle closest to the pickup location of the logistics order in chronological order; Step S103: setting the current position of the logistics shuttle as the starting point of the logistics shuttle, setting the pickup position of the logistics order as the stop point of the logistics shuttle, and setting the delivery position of the logistics order as the end point of the logistics shuttle; The step S2 includes the following sub-steps: Step S201: Real-time acquisition of the number of logistics shuttles in the storage area, marking the logistics shuttles, and obtaining the logistics shuttles CS1 to CS2. n ; Step S202: Logistics shuttle CS1 to logistics shuttle CS n Set up m sub-simulation cars respectively, marked as CS i -Z1 to CS i -Z m , where the value of i ranges from 1 to n; The step S3 includes the following sub-steps: Step S301: Obtain a plan view of the storage area, obtain the path that the logistics shuttle vehicle can pass through in the storage area, and obtain a map to be planned; Step S302: Get any logistics shuttle CS i The starting point, stop point and end point; Step S303: Obtain the logistics shuttle CS i All paths from the starting point to the stop point are set as a path; Get Logistics Shuttle CS i All paths from the stop point to the end point are set as two-segment paths; Get all combinations of the first path and the second path to get the sub-simulation path, and arrange an arbitrary sub-simulation car CS for each sub-simulation path i -Z l ; Wherein, the value of l ranges from 1 to m; Step S304: For any sub-simulated vehicle CS i -Z l Record the time of the trip on the sub-simulation path to obtain a time mark; The time record in step S304 includes a plane mark and a z-axis mark, and the plane mark includes: obtaining the logistics shuttle CS i Body length, when any sub-simulation car CS i -Z l Each distance traveled on the plane of the sub-simulation path is equal to the logistics shuttle CS i When the path is the length of the vehicle body, the path is recorded as a plane grid, and a plane time mark is left for the plane grid. The plane time mark is the sub-simulation vehicle CS i -Z l The time point of entering the plane grid; until all the paths on the plane of the path are recorded as plane grids and leave plane time marks; The z-axis marking includes: obtaining the logistics shuttle CS i Vehicle height, when any sub-simulation vehicle CS i -Z l Each distance traveled on the z-axis path of the sub-simulation path is equal to the logistics shuttle CS i When the path of the vehicle body height is recorded, the path is recorded as a z-axis square, and a z-axis time mark is left for the z-axis square. The z-axis time mark is the sub-simulation vehicle CS i -Z l The time point of entering the z-axis grid; until all z-axis paths of the path are recorded as z-axis grids and leave z-axis time marks; The step S4 includes the following sub-steps: Step S401: obtaining the number of squares on each sub-simulation path and recording it as the path length of the sub-simulation path, wherein the squares on each sub-simulation path include z-axis squares and plane squares; Step S402: Obtain the path lengths of all sub-simulation paths, sort the path lengths in ascending order, and mark the importance level of each sub-simulation path according to the sorting, wherein the shorter the path length, the higher the importance level; Step S403: obtaining the first number of sub-simulation paths with the highest importance level for each logistics shuttle vehicle, marking them on the map to be planned, and obtaining a simulation map; The step S5 includes the following sub-steps: Step S501: Obtain the time sequence of the logistics orders received by all logistics shuttles, and set the time sequence of the logistics orders as the priority sequence of the logistics shuttles; Step S502: setting the sub-simulation path with the highest importance level of the logistics shuttle vehicle with the highest current priority order as the first-level path, and obtaining the time marks of all the squares on the first-level path; Step S503: when the time marks of all squares on the primary path are independent and different, the primary path is retained and set as the selected path, and the logistics shuttle with the highest priority is removed from the priority order of the logistics shuttle; When the same time mark appears on any square on the primary path, the primary path is retained and set as the selected path, the square is set as a divergence square, all sub-simulation paths corresponding to the same time mark are set as secondary paths, and the secondary paths are optimized to obtain a secondary path cancellation signal or a secondary path delay signal; Step S504: when a secondary path cancellation signal is received, after deleting the secondary path, the logistics shuttle with the highest current priority order is removed from the priority order of logistics shuttles; When a secondary path delay signal is received, the secondary path obtained after the delay modification is set as the selection path of the corresponding logistics shuttle, and the logistics shuttle with the highest current priority and the logistics shuttle corresponding to the secondary path obtained after the delay modification are removed from the priority order of the logistics shuttle; Step S505: repeating steps S501 to S504 until all logistics shuttles are removed from the priority order of logistics shuttles; The secondary path optimization includes obtaining a logistics shuttle vehicle corresponding to any secondary path, obtaining the shortest path of the logistics shuttle vehicle on the simulation map, and recording the time of the marking moment on the last square of the shortest path as the route switching time; Obtain any secondary path, and set an extension time for the secondary path, where the extension time is the difference between the time mark of the next square of the divergent square on the primary path and the time mark on the divergent square; Performing a delay modification on the time mark on the square behind the divergent square on the secondary path, wherein the delay modification includes adding an extended time to the time of the original time mark, and setting the time mark obtained after the delay modification as a secondary mark; The time to obtain the secondary mark of the last square on the secondary path is recorded as the waiting time; When the switching time is earlier than the waiting time, a secondary path cancellation signal is sent; When the route switching time is later than the waiting time, the modified secondary path is merged into the simulation map, and it is determined whether the secondary path obtained after the delay modification has the same time mark as other simulation paths on the simulation map; When the secondary path obtained after the delay modification does not have the same time mark as other simulated paths on the simulated map, a secondary path delay signal is sent; When the secondary path obtained after delay modification appears at the same time mark as other simulated paths on the simulated map, a secondary path cancellation signal is sent.

2. A logistics shuttle path optimization system based on an ant colony optimization algorithm, used to implement the logistics shuttle path optimization method based on an ant colony optimization algorithm of claim 1, characterized in that: include: Logistics distribution module, route collection module, route marking module and route optimization module; The logistics distribution module is used to distribute logistics orders to logistics shuttle vehicles; The path acquisition module is used to set up a sub-simulation vehicle for the logistics shuttle vehicle and use the sub-simulation vehicle to construct a simulation path; The path marking module is used to mark the simulation path to obtain the time mark and the importance level of the simulation path; The path optimization module is used to obtain the priority order of the logistics shuttle vehicles and optimize the paths of the logistics shuttle vehicles according to the priority order of the logistics shuttle vehicles.

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